CN113283791B - Method, device, equipment and storage medium for selecting self-lifting cabinet characteristics - Google Patents
Method, device, equipment and storage medium for selecting self-lifting cabinet characteristics Download PDFInfo
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Abstract
The invention provides a method, a device, equipment and a storage medium for selecting self-lifting cabinet characteristics, which comprises the following steps: calculating a cabinet-out rate parameter of the self-cabinet-lifting feature of at least one dimension according to the historical logistics order information; and selecting the self-lifting cabinet characteristics according to the cabinet outlet rate parameters of the self-lifting cabinet characteristics. According to the invention, through analyzing the historical logistics order information, proper self-lifting cabinet characteristics are selected, and the cabinet outlet rate of the self-lifting cabinet is improved, so that the utilization rate of the self-lifting cabinet is improved.
Description
Technical Field
The present invention relates to the field of computer applications, and in particular, to a method, apparatus, device, and storage medium for selecting self-extracting features.
Background
At present, when a logistics terminal express delivery person carries out parcel delivery, the situation that a receiver is not at a receiving address is often encountered, and for this purpose, the express delivery person can select a self-lifting cabinet mode to carry out parcel delivery, so that the dispatching efficiency of the express delivery person is improved through an asynchronous delivery mode, and the user is facilitated.
However, in the analysis of the signing status of the logistic packages, it is found that the user often cannot timely take the packages out of the self-lifting cabinet, and even the condition that the storage of the self-lifting cabinet is overtime and the packages are re-delivered by the courier occurs. Therefore, the utilization rate of the self-lifting cabinet is reduced, and the additional workload of couriers is increased.
Therefore, how to improve the utilization rate of the self-lifting cabinet through analysis of the historical logistics order information is a technical problem to be solved in the field.
Disclosure of Invention
In order to overcome the defects of the related art, the invention provides a method, a device, equipment and a storage medium for selecting the characteristics of a self-lifting cabinet, and further improves the utilization rate of the self-lifting cabinet through analysis of historical logistics order information.
According to one aspect of the invention, there is provided a method of selecting a self-extracting feature, comprising:
calculating a cabinet-out rate parameter of the self-cabinet-lifting feature of at least one dimension according to the historical logistics order information;
and selecting the self-lifting cabinet characteristics according to the cabinet outlet rate parameters of the self-lifting cabinet characteristics.
In some embodiments of the present invention, the calculating the cabinet output parameter of the self-service cabinet feature of at least one dimension according to the historical logistics order information includes:
acquiring the state of the in-and-out cabinet of the logistics package according to the logistics track information of the historical logistics order information;
acquiring self-lifting cabinet characteristics of at least one dimension according to the historical logistics order information;
and calculating a cabinet rate parameter according to the self-cabinet lifting characteristics of at least one dimension based on the in-out state of the logistics package of the historical logistics order information.
In some embodiments of the present invention, the acquiring self-contained cabinet features of at least one dimension according to the historical logistics order information includes:
acquiring logistics track information containing history logistics order information of the entered cabinet according to the history logistics order information;
Acquiring information of a self-lifting cabinet of each piece of history logistics order information;
and acquiring self-lifting cabinet characteristics of at least one dimension according to the information of the self-lifting cabinet.
In some embodiments of the invention, the bin out rate parameter comprises a first bin out rate and a second bin out rate, the first bin out rate and the second bin out rate being distinguished by a time difference in the in-out of the logistic package.
In some embodiments of the present invention, before calculating the cabinet output parameter of the self-service cabinet feature of at least one dimension according to the historical logistics order information, the method includes:
A logistics order generation request is received by a logistics order system,
The cabinet outlet rate parameters according to the self-cabinet characteristics comprise the following steps:
the selected self-cabinet feature is sent to the logistics order system to generate a logistics order in accordance with the selected self-cabinet feature.
In some embodiments of the invention, the logistics order system comprises an electronic facial sheet printing system.
In some embodiments of the invention, the selecting the self-extracting feature according to the bin yield parameter of the self-extracting feature includes:
according to the set dimension, the self-extracting cabinet characteristic with the highest cabinet-extracting rate parameter is selected from the cabinet-extracting rate parameters of the self-extracting cabinet characteristics of the dimension.
In some embodiments of the invention, the bin yield parameter of the self-extracting bin feature is calculated based on a plurality of dimensions, the method further comprising:
according to the cabinet outlet rate parameters of the self-extracting cabinet characteristics of multiple dimensions, determining the dimension with the largest influence on the cabinet outlet rate parameters;
And determining an optimization scheme of the self-lifting cabinet characteristics of the dimension according to the cabinet outlet rate parameters of the self-lifting cabinet characteristics of the dimension.
In some embodiments of the present invention, after calculating the cabinet output parameter of the self-service cabinet feature of at least one dimension according to the historical logistics order information, the method further includes:
judging whether the cabinet outlet rate parameter of the self-lifting cabinet characteristic is smaller than a set threshold value;
if yes, generating alarm information.
In some embodiments of the invention, the step of calculating the bin yield parameter of the self-extracting bin feature of at least one dimension based on the historical logistics order information is performed periodically.
In some embodiments of the invention, the self-extracting bin feature includes one or more of the following dimensions: the method comprises the steps of providing a self-lifting cabinet provider, saving information of a city where the self-lifting cabinet is located, informing a user of a goods taking mode, charging whether the self-lifting cabinet is charged, and the self-lifting cabinet size and the self-lifting cabinet number.
According to yet another aspect of the present invention, there is also provided an apparatus for selecting self-contained features, comprising:
The calculation module is configured to calculate the cabinet-out rate parameter of the self-cabinet-lifting feature of at least one dimension according to the historical logistics order information;
and the selection module is configured to select the self-lifting cabinet characteristic according to the cabinet outlet rate parameter of the self-lifting cabinet characteristic.
According to still another aspect of the present invention, there is also provided an electronic apparatus including: a processor; a storage medium having stored thereon a computer program which, when executed by the processor, performs the steps as described above.
According to a further aspect of the present invention there is also provided a storage medium having stored thereon a computer program which, when executed by a processor, performs the steps as described above.
Compared with the prior art, the invention has the advantages that:
According to the method, the automatic cabinet taking-out rate parameter of the automatic cabinet taking-out characteristics of at least one dimension is calculated based on the historical logistics order information, and the automatic cabinet taking-out characteristics are selected according to the automatic cabinet taking-out rate parameter of the automatic cabinet taking-out characteristics, so that the automatic cabinet taking-out rate is improved by selecting proper automatic cabinet taking-out characteristics through analysis of the historical logistics order information, and the utilization rate of the automatic cabinet taking-out is improved.
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The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
FIG. 1 illustrates a flow chart of a method of selecting self-contained features according to an embodiment of the present invention.
FIG. 2 illustrates a flow chart for calculating a bin yield parameter for a self-extracting bin feature of at least one dimension based on historical logistics order information, in accordance with an embodiment of the present invention.
FIG. 3 illustrates a flow chart of acquiring self-contained cabinet features of at least one dimension from the historical logistics order information, in accordance with an embodiment of the present invention.
FIG. 4 illustrates a flow chart of an optimization scheme for determining self-contained features in a method for selecting self-contained features according to an embodiment of the invention.
Fig. 5 shows a block diagram of an apparatus for selecting self-contained features according to an embodiment of the present invention.
Fig. 6 schematically illustrates a computer-readable storage medium according to an exemplary embodiment of the present invention.
Fig. 7 schematically illustrates an electronic device according to an exemplary embodiment of the invention.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Furthermore, the drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor devices and/or microcontroller devices.
The flow diagrams depicted in the figures are exemplary only and not necessarily all steps are included. For example, some steps may be decomposed, and some steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.
In various embodiments of the present invention, the method for selecting self-lifting features provided in the present invention may be applied to a logistics platform, an electronic commerce platform, or any platform provided by a third party for selecting and optimizing self-lifting features, but the application scenario of the present invention is not limited thereto and will not be described herein.
FIG. 1 illustrates a flow chart of a method of selecting self-contained features according to an embodiment of the present invention. The method for selecting the self-lifting cabinet characteristics comprises the following steps:
Step S110: and calculating the cabinet-out rate parameter of the self-cabinet-lifting feature of at least one dimension according to the historical logistics order information.
In particular, the self-extracting bin feature may include one or more of the following dimensions: the invention is not limited to the above, and other self-lifting features are within the scope of the invention. Specifically, the self-carrying case features specific feature data in one or more of the aforementioned dimensions. For example, in the dimension of notifying the user of the mode of pickup, the self-cabinet feature may be a SMS notification, a telephone notification, an APP push, an applet message, and the like. The corresponding crowd of the self-lifting cabinet can correspond to different pickup crowd according to business circles, office buildings and residences to which the address of the self-lifting cabinet belongs.
Specifically, the cabinet outlet rate parameter is used for representing the ratio of the number of the packages which are taken out of the cabinet to the number of the packages which are taken in the cabinet within the set cabinet inlet and outlet time difference under the self-lifting cabinet characteristic of each dimension. Specifically, the set cabinet time difference can be set as needed. For example, the time difference of the in-and-out cabinet may be set to one day, and the proportion of the number of packages taken out to the in-and-out cabinet within one day from the in-and-out cabinet time; for another example, the time difference between the in and out of the cabinet may be set to two days, and the package taken out within two days from the in-cabinet time accounts for the proportion of the number of packages in the cabinet; for another example, the time difference of the in-and-out cabinet may be set to the time of charging from the cabinet according to the time difference of the in-and-out cabinet of the charging time from the cabinet.
Furthermore, in order to perform more detailed analysis on the package cabinet-out rate parameters, the cabinet-out rate parameters can include a first cabinet-out rate and a second cabinet-out rate, and the first cabinet-out rate and the second cabinet-out rate are distinguished according to the cabinet-in and cabinet-out time difference of the logistic package. In one implementation, the difference in cabinet time for the first cabinet out rate may be set to one day; and setting the cabinet entering and exiting time difference of the second cabinet exiting rate to be two days. In other implementations, the in-and-out time difference for the first out-rate may be set to the time to charge from the pick up (e.g., 18 hours); the time difference of the second out-of-cabinet rate is set to the sum of the time taken to charge from the pick-up cabinet and the charging unit time (for example, the charge is started from the pick-up cabinet after the package is put in the cabinet for 18 hours, the charge is increased by 1 yuan every 6 hours, then the time difference of the second out-of-cabinet rate can be set to the sum of 18 hours and 6 hours, namely 24 hours). The invention is not limited thereto, and the cabinet-out rate parameter may include more cabinet-out rates to achieve finer differentiation of cabinet-out time differences.
Further, the cabinet-out rate parameter is calculated by taking the cabinet-in packages as the total number, so that each feature is more sensitive to the change of the cabinet-out rate data, and the selection of the cabinet-out features and the subsequent determination of the optimization scheme of the cabinet-out features are more convenient to perform compared with the case that the number of packages which are not sent by the cabinet-out is included in the total number of packages.
The set access time difference for the first rate may be less than the set access time difference for the second rate. In this embodiment, the second cabinet output rate may include the first cabinet output rate. In other words, the second delivery rate is the ratio of the number of packages taken out to the number of packages already in the cabinet within the set delivery time difference of the second delivery rate. In other embodiments, the second rate may not include the first rate. In other words, the second delivery rate is the ratio of the number of packages taken out to the number of packages already delivered after the set delivery time difference of the first delivery rate and before the set delivery time difference of the second delivery rate. The invention can set the cabinet outlet rate parameter according to the need, and is not described in detail herein.
Step S120: and selecting the self-lifting cabinet characteristics according to the cabinet outlet rate parameters of the self-lifting cabinet characteristics.
Thus, step S120 may select the self-extracting features with higher extracting rate parameters according to the extracting rate parameters of the respective extracting features. In some embodiments, the selected self-cabinet feature may be automatically updated into the logistics order to enable the logistics order to determine the self-cabinet and related self-cabinet parameters at the end of the logistics in accordance with the selected self-cabinet feature. In other embodiments, the selected self-contained features are provided to the sender user or the user of the e-commerce purchase as recommended self-contained features, so that the user can select and set the self-contained features according to the recommended self-contained features and according to actual conditions.
Further, according to the difference of execution bodies of the method for selecting the self-lifting cabinet characteristics, after the selected self-lifting cabinet characteristics are obtained, the selected self-lifting cabinet characteristics can be sent to different platforms. For example, when the method of selecting self-cabinet features is performed by the e-commerce platform, after obtaining the selected self-cabinet features, the e-commerce platform may provide the selected self-cabinet features to the user as recommended self-cabinet features; or generating a logistics order directly according to the selected self-lifting cabinet characteristics, and sending the logistics order to a logistics platform. For example, when the method of selecting self-cabinet features is performed by a logistics platform, a logistics order can be generated directly from obtaining the selected self-cabinet features, and the generated logistics order can be synchronized to the sender user and the receiver user. The present invention may implement more variations, and will not be described in detail herein.
Specifically, in one specific implementation of the present invention, prior to step S110, a method of selecting a self-contained feature may perform: a logistics order generation request is received by a logistics order system. So that after step S130 it may be performed to send the selected self-cabinet feature to the logistics order system to generate a logistics order in accordance with the selected self-cabinet feature. Therefore, the automatic selection of the self-cabinet-lifting characteristics is realized, and the step of generating the logistics order according to the self-cabinet-lifting characteristics is realized, so that the generation efficiency of the logistics order and the intelligence of generating the logistics order are improved on the basis of improving the cabinet-lifting rate of the self-cabinet. Further, the logistics order system can comprise an electronic face sheet printing system, and therefore the electronic face sheet printing system can print electronic face sheets directly according to the generated logistics order. The selected self-lifting cabinet features can be printed on the logistics face sheet for the sender to intuitively know, and package dispatch is performed according to the selected self-lifting cabinet features. In this implementation, the logistics order system may be a logistics order system of a logistics platform, or may be a logistics order system of an e-commerce platform interacting with the logistics platform, which is not limited by the present invention.
Specifically, when the self-contained cabinet feature includes multiple dimensions, step S120 may be implemented as follows: according to the set dimension, the self-extracting cabinet characteristic with the highest cabinet-extracting rate parameter is selected from the cabinet-extracting rate parameters of the self-extracting cabinet characteristics of the dimension. For example, the dimension of the self-carrying cabinet provider may be set, and the self-carrying cabinet provider with the highest cabinet outlet rate parameter is selected as the selected self-carrying cabinet feature according to the cabinet outlet rate parameters of different self-carrying cabinet providers. In some variations, multiple dimensions may be set, and the self-extracting features with the highest cabinet-extracting parameters are selected from the cabinet-extracting parameters of the self-extracting features in the dimensions, so as to obtain a combination of the self-extracting features. When the obtained self-cabinet feature combinations contradict, for example, the self-cabinet feature combinations include a self-cabinet provider and a number of self-cabinets, however, when the number of self-cabinets of the self-cabinet provider near the destination address of the current order is not equal to the determined number of self-cabinets, priorities of different dimensions may be set, based on the self-cabinet features of the higher-priority dimensions.
According to the method for selecting the self-lifting cabinet characteristics, the cabinet outlet rate parameter of the self-lifting cabinet characteristics with at least one dimension is calculated based on the historical logistics order information, and the self-lifting cabinet characteristics are selected according to the cabinet outlet rate parameter of the self-lifting cabinet characteristics, so that the proper self-lifting cabinet characteristics are selected through analysis of the historical logistics order information, the cabinet outlet rate of the self-lifting cabinet is improved, and the utilization rate of the self-lifting cabinet is improved.
Referring now to fig. 2, fig. 2 illustrates a flow chart for grouping users based on address information of the users according to an embodiment of the present invention. Fig. 2 shows the following steps in total:
step S111: and acquiring the state of the in-and-out cabinet of the logistics package according to the logistics track information of the historical logistics order information.
Specifically, the historical logistics order information may be obtained according to a set time. For example, historical logistics order information of the last n days (n is an integer of 1 or more) may be acquired; for another example, historical logistics order information for a set period of time may be obtained. Further, the historical logistics order information may be based on the logistics order setup time. In other words, for a current shipping state, but the logistics order information for which the logistics order set-up time is within the set time period may also belong to the historical logistics order information.
Specifically, since the logistics platform stores each logistics order information and the logistics track information thereof, the step S111 can acquire information from the related database of the logistics platform. In some variations, the e-commerce platform may synchronize with the logistics platform to store the information of each logistics order and the information of the logistics track associated with the e-commerce order, so step S111 may also perform information acquisition from the relevant database of the e-commerce platform.
Specifically, the logistics track information of the historical logistics order information comprises whether the package is dispatched by the self-lifting cabinet or not, and if the package is dispatched by the self-lifting cabinet, the logistics track information of the historical logistics order information further comprises the current state of the package in-cabinet or out-cabinet (comprising the time of the package in-cabinet and the time of the package out-cabinet). Further, in some embodiments, the out-cabinet state includes taking out by the user and taking out by the courier, and since the present disclosure is mainly used to improve the out-cabinet rate of the user taking out, it is preferable that the out-cabinet state in each embodiment of the present disclosure refers to the user taking out.
Step S112: and acquiring self-lifting cabinet characteristics of at least one dimension according to the historical logistics order information.
Step S112 may be implemented by a flowchart shown in fig. 3, which is not described herein.
Step S113: and calculating a cabinet rate parameter according to the self-cabinet lifting characteristics of at least one dimension based on the in-out state of the logistics package of the historical logistics order information.
Specifically, when the self-extracting feature has a plurality of dimensions, step S113 may perform calculation of the bin yield parameter for the self-extracting feature of the plurality of dimensions. For example, the cabinet output rate parameters of the self-provided cabinet provider can be calculated according to different self-provided cabinet providers respectively; according to different modes of informing a user of taking goods, calculating the cabinet outlet rate parameters of the self-lifting cabinet provider respectively; according to different sizes of the self-lifting cabinets, the cabinet outlet rate parameters of the self-lifting cabinet provider are calculated respectively, and the invention is not limited by the parameters.
Referring now to FIG. 3, FIG. 3 illustrates a flow chart for acquiring at least one dimension of self-contained bin characteristics based on the historical logistics order information. Fig. 3 shows the following steps in total:
step S1121: and acquiring the historical logistics order information containing the entered cabinet according to the historical logistics order information.
Specifically, since the present case preferably calculates only the logistics orders dispatched via the self-lifting cabinets, one at a time you perform screening of the logistics orders by means of the logistics trajectory information through step S1121.
Further, in some embodiments of the present invention, the method may further include cleaning the historical logistics order information before step S1121, for example, deleting the historical logistics order information such as abnormal logistics track information, abnormal order sign-up, etc., so as to reduce the number of subsequent data processing and improve the execution efficiency of the method.
Step S1122: and acquiring information of the self-contained cabinets of the historical logistics order information.
Step S1123: and acquiring self-lifting cabinet characteristics of at least one dimension according to the information of the self-lifting cabinet.
In particular, in some embodiments, the information of the self-contained cabinets may include, for example, an identification of the self-contained cabinets, whereby the self-contained cabinet features of each dimension may be extracted from a self-contained cabinet feature database based on the identification of the self-contained cabinets. In other words, in this embodiment, there is no need to store corresponding self-service cabinet features for the historical logistics order information, reducing the data storage volume, and in some variations, the self-service cabinet features include static features (size, number, self-service cabinet provider, etc.) and dynamic features (notifying the user of the way to pick up the goods, whether the self-service cabinet charges). In this embodiment, the dynamic features of the self-contained cabinets may be stored in association with historical logistics orders, while the static features may be stored in a self-contained cabinet feature database, thereby enabling to cope with the acquisition of static and dynamic features and to optimize feature storage.
Referring now to fig. 4, fig. 4 is a flow chart illustrating an optimization scheme for determining self-contained features in a method for selecting self-contained features according to an embodiment of the present invention. Fig. 4 shows the following steps in total:
Step S130: and determining the dimension with the largest influence on the cabinet outlet rate parameter according to the cabinet outlet rate parameters of the self-lifting cabinet characteristics of the plurality of dimensions.
Specifically, the dimension that affects the cabinet-out rate parameter to the greatest extent can be determined as follows: and calculating the square difference of the cabinet-outlet rate parameters of the self-cabinet-lifting characteristics of each dimension, thereby taking the square difference as the influence degree, and determining the dimension with the largest influence degree as the dimension with the largest influence degree on the cabinet-outlet rate parameters.
In some variations, for each dimension, the difference between the minimum and maximum cabinet-out parameters of the self-lifting characteristics of that dimension may also be calculated, so that the difference is taken as the influence, and the dimension with the greatest influence is determined as the dimension with the greatest influence on the cabinet-out parameters.
The invention is not limited thereto, and other ways of calculating the influence are within the scope of the invention.
Step S140: and determining an optimization scheme of the self-lifting cabinet characteristics of the dimension according to the cabinet outlet rate parameters of the self-lifting cabinet characteristics of the dimension.
Specifically, taking a goods taking mode of a self-provided cabinet informing user as an example, when the cabinet outlet rate parameter of a short message informing is 50%, the cabinet outlet rate parameter of a telephone informing is 70%, the cabinet outlet rate parameter of an APP pushing is 60%, and the cabinet outlet rate parameter of a small program message is 65%, the telephone informing can be used as an optimization scheme of the self-provided cabinet feature of the dimension, and the optimization scheme can be sent to a server, a logistics platform or an electronic commerce platform of a self-provided provider so as to be convenient to adjust and optimize.
Taking the number of self-lifting cabinets as an example, when the number of self-lifting cabinets is 50% of cabinet outlet rate parameters of 1 cabinet, when the number of self-lifting cabinets is 60% of cabinet outlet rate parameters of 2 cabinets, when the number of self-lifting cabinets is 60% of cabinet outlet rate parameters of 3 cabinets, the number of self-lifting cabinets can be 3 cabinets (or the number of self-lifting cabinets is proportional to the cabinet outlet rate) as an optimization scheme of the self-lifting cabinet characteristics of the dimension, and the optimization scheme is sent to a server of a self-lifting cabinet provider so that the number of the self-lifting cabinets in various places can be increased according to demands by the self-lifting cabinet provider.
The foregoing is merely illustrative of an optimization scheme for the self-contained cabinet features of the present invention, and the present invention is not limited thereto.
In some embodiments of the present invention, after step S110, it may further include: judging whether the cabinet outlet rate parameter of the self-lifting cabinet characteristic is smaller than a set threshold value; if yes, generating alarm information. Thus, the self-contained features are monitored and alerted according to the set threshold. For example, when the rate of delivery of the short message notification is less than 40%, the rate of delivery of the short message notification will affect the delivery efficiency of the self-contained cabinet, and thus, an alarm message may be generated to alert the replacement of the feature. For example, the self-extracting features generating the alarm information may be replaced according to the optimization scheme of the previous embodiment or the self-extracting features selected in step S120, so as to further improve the self-extracting cabinet rate.
In some embodiments of the present invention, the step of step S110 is performed periodically, so that the generation of the optimization scheme of fig. 4 and the monitoring of the cabinet output rate of the self-lifting cabinet feature of the previous embodiment may be performed periodically, thereby implementing monitoring and alarming. And (5) closing an optimized service.
In one specific implementation of the present invention, the method of selecting self-extracting features may be implemented as follows: first, prepare the self-lifting cabinet data dimension: the configuration of the related attributes of the self-lifting cabinets is completed by providing the self-lifting cabinets, saving the information of the city area where the self-lifting cabinets are located, informing the user of the goods taking mode (short message, telephone, APP pushing), charging whether the self-lifting cabinets are charged, the size of the self-lifting cabinets, the number of the self-lifting cabinets and the like. A real-time computing platform and/or an offline analysis platform (to perform the method of selecting self-cabinet features) may then be built. When the e-commerce platform receives the user order, a message component is used to send the user order information. And storing the electronic face sheet information and sending the electronic face sheet information to a real-time computing platform and an offline analysis platform. Track information of a logistics company is monitored, express delivery cabinet information is filtered out, and the express delivery cabinet information is sent to a real-time computing platform and an offline analysis platform. The real-time computing platform and the offline analysis platform can be configured with dimension information, and the order quantity and total order quantity of the e-commerce platform orders in the dimension cabinet outlet are computed, so that the daily cabinet outlet rate and the daily cabinet outlet rate are computed. The dimension with the largest deviation is found out from various dimensions affecting the cabinet outlet rate for improvement, for example, the cabinet outlet rate is affected by the dimension of the size of the self-lifting cabinets, and the cabinet outlet rate can be improved by increasing the number of the self-lifting cabinets, preparing large self-lifting cabinets and the like. And finally, feeding the analysis data back to the electronic bill system of the electronic commerce platform, so that a self-lifting cabinet provider with higher cabinet rate can be selected when the electronic bill is printed.
The foregoing is illustrative of a particular implementation of the invention, and the invention is not so limited. In various embodiments of the invention, the method of selecting self-cabinet features may be implemented by a real-time computing platform and/or an offline analysis platform. In some implementations, the real-time computing platform may perform selection of self-contained features to enable faster acquisition of self-contained features for order generation and printing of the order; the real-time computing platform may also perform real-time monitoring and alerting. The offline analysis platform can realize the determination of an optimization scheme of the self-cabinet characteristics so as to execute data analysis with relatively low real-time requirements.
In other specific implementations, the offline analysis platform may perform calculation of the cabinet output rate parameter in advance, and store the calculation result, so that the real-time calculation platform can implement selection of the self-cabinet feature, real-time monitoring and alarming, and determination of the self-cabinet feature optimization scheme based on the cabinet output rate parameter of the offline analysis platform. Therefore, the execution efficiency of the whole business closed loop is improved through the step division and combination of the off-line analysis platform and the real-time calculation platform.
The foregoing is merely a plurality of specific implementations of the method for selecting self-contained features of the invention, each implementation may be implemented independently or in combination, and the invention is not limited thereto. Further, the flow chart of the present invention is merely illustrative, and the execution order of steps is not limited thereto, and the splitting, merging, sequential exchange, and other synchronous or asynchronous execution of steps are all within the scope of the present invention.
Referring now to fig. 5, fig. 5 shows a block diagram of an apparatus for selecting self-contained features according to an embodiment of the present invention. The apparatus 200 for selecting self-contained features includes a computing module 210 and a selecting module 220.
The calculation module 210 is configured to calculate a cabinet yield parameter of the self-cabinet feature of at least one dimension according to the historical logistics order information;
the selection module 220 is configured to select the self-extracting feature based on the bin yield parameter of the self-extracting feature.
In the device for selecting the self-lifting features according to the exemplary embodiment of the invention, the self-lifting features are selected according to the cabinet-lifting rate parameters of the self-lifting features by calculating the cabinet-lifting rate parameters of the self-lifting features of at least one dimension based on the historical logistics order information, so that the proper self-lifting features are selected through analysis of the historical logistics order information, the cabinet-lifting rate of the self-lifting cabinet is improved, and the utilization rate of the self-lifting cabinet is improved.
Fig. 5 is a schematic illustration of the apparatus 200 for selecting self-carrying case features provided by the present invention, and the splitting, merging and adding of modules are all within the scope of the present invention without departing from the concept of the present invention. The device 200 for selecting self-lifting features provided in the present invention may be implemented by software, hardware, firmware, plug-ins, and any combination thereof, which is not limited to this embodiment.
In an exemplary embodiment of the invention, a computer readable storage medium is also provided, on which a computer program is stored, which program, when being executed by a processor, for example, can implement the steps of the method of selecting self-extracting features as described in any of the above embodiments. In some possible embodiments, the aspects of the invention may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the invention as described in the above-mentioned method section of selecting self-extracting features, when said program product is run on a terminal device.
Referring to fig. 6, a program product 700 for implementing the above-described method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable storage medium may also be any readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the tenant computing device, partially on the tenant device, as a stand-alone software package, partially on the tenant computing device, partially on a remote computing device, or entirely on a remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the tenant computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected through the internet using an internet service provider).
In an exemplary embodiment of the invention, an electronic device is also provided, which may include a processor, and a memory for storing executable instructions of the processor. Wherein the processor is configured to perform the steps of the method of selecting self-contained features of any of the embodiments described above via execution of the executable instructions.
Those skilled in the art will appreciate that the various aspects of the invention may be implemented as a system, method, or program product. Accordingly, aspects of the invention may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may be referred to herein as a "circuit," module "or" system.
An electronic device 500 according to this embodiment of the invention is described below with reference to fig. 7. The electronic device 500 shown in fig. 7 is merely an example, and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 7, the electronic device 500 is embodied in the form of a general purpose computing device. The components of electronic device 500 may include, but are not limited to: at least one processing unit 510, at least one memory unit 520, a bus 530 connecting the different system components (including the memory unit 520 and the processing unit 510), a display unit 540, etc.
Wherein the storage unit stores program code that is executable by the processing unit 510 such that the processing unit 510 performs the steps according to various exemplary embodiments of the invention described in the above-described method section of selecting self-contained features of the present specification. For example, the processing unit 510 may perform the steps shown in any one or more of fig. 1-4.
The memory unit 520 may include readable media in the form of volatile memory units, such as Random Access Memory (RAM) 5201 and/or cache memory unit 5202, and may further include Read Only Memory (ROM) 5203.
The storage unit 520 may also include a program/utility 5204 having a set (at least one) of program modules 5205, such program modules 5205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
Bus 530 may be one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
The electronic device 500 may also communicate with one or more external devices 600 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a tenant to interact with the electronic device 500, and/or any device (e.g., router, modem, etc.) that enables the electronic device 500 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 550. Also, electronic device 500 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 560. The network adapter 560 may communicate with other modules of the electronic device 500 via the bus 530. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 500, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the solution according to the embodiments of the present invention may be embodied in the form of a software product, which may be stored on a non-volatile storage medium (which may be a CD-ROM, a usb disk, a mobile hard disk, etc.), or on a network, comprising several instructions to cause a computing device (which may be a personal computer, a server, or a network device, etc.) to perform the above-described method of selecting self-lifting features according to embodiments of the present invention.
Compared with the prior art, the invention has the advantages that:
According to the method, the automatic cabinet taking-out rate parameter of the automatic cabinet taking-out characteristics of at least one dimension is calculated based on the historical logistics order information, and the automatic cabinet taking-out characteristics are selected according to the automatic cabinet taking-out rate parameter of the automatic cabinet taking-out characteristics, so that the automatic cabinet taking-out rate is improved by selecting proper automatic cabinet taking-out characteristics through analysis of the historical logistics order information, and the utilization rate of the automatic cabinet taking-out is improved.
Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
Claims (11)
1. A method of selecting a self-contained feature, comprising:
Receiving, by a logistics order system, a logistics order generation request;
According to the historical logistics order information, calculating the cabinet-out rate parameter of the self-cabinet-lifting feature of at least one dimension, comprising: acquiring the in-and-out state of the logistics package according to the logistics track information of the historical logistics order information, acquiring the self-cabinet-lifting characteristics of at least one dimension according to the historical logistics order information, and calculating a cabinet rate parameter according to the self-cabinet-lifting characteristics of at least one dimension and the in-and-out state of the logistics package based on the historical logistics order information; the out-of-cabinet state of the logistics package is taken out by a user;
Wherein the self-extracting cabinet feature comprises one or more of the following dimensions: the method comprises the steps of providing a self-picking cabinet provider, information of a city area where the self-picking cabinet is located, informing a user of a goods taking mode, whether the self-picking cabinet is charged, the size of the self-picking cabinet, the number of the self-picking cabinets and corresponding crowds of the self-picking cabinets, wherein the cabinet outlet rate parameter represents the ratio of the number of the packages which are taken out of the cabinet to the number of the packages which are taken into the cabinet in a set cabinet outlet time difference under the self-picking cabinet characteristics of each dimension;
selecting the self-extracting cabinet characteristics according to the cabinet outlet rate parameters of the self-extracting cabinet characteristics;
the selected self-cabinet feature is sent to the logistics order system to generate a logistics order in accordance with the selected self-cabinet feature.
2. The method of selecting self-cabinet features of claim 1, wherein said obtaining self-cabinet features of at least one dimension from said historical logistics order information comprises:
acquiring logistics track information containing history logistics order information of the entered cabinet according to the history logistics order information;
Acquiring information of a self-lifting cabinet of each piece of history logistics order information;
and acquiring self-lifting cabinet characteristics of at least one dimension according to the information of the self-lifting cabinet.
3. The method of selecting self-extracting features of claim 1, wherein the bin out rate parameter comprises a first bin out rate and a second bin out rate, the first bin out rate being distinguished from the second bin out rate by a time difference in bin out of a logistic package.
4. The method of selecting self-cabinet features of claim 1, wherein said logistics order system comprises an electronic facial sheet printing system.
5. The method of selecting self-extracting features of claim 1, wherein selecting self-extracting features based on the bin yield parameters of the self-extracting features comprises:
according to the set dimension, the self-extracting cabinet characteristic with the highest cabinet-extracting rate parameter is selected from the cabinet-extracting rate parameters of the self-extracting cabinet characteristics of the dimension.
6. The method of selecting a self-cabinet feature of claim 1, wherein a cabinet-out rate parameter of the self-cabinet feature is calculated based on a plurality of dimensions, the method further comprising:
according to the cabinet outlet rate parameters of the self-extracting cabinet characteristics of multiple dimensions, determining the dimension with the largest influence on the cabinet outlet rate parameters;
And determining an optimization scheme of the self-lifting cabinet characteristics of the dimension according to the cabinet outlet rate parameters of the self-lifting cabinet characteristics of the dimension.
7. The method of selecting self-cabinet features of claim 1, wherein after calculating the cabinet-out rate parameter of the self-cabinet features of at least one dimension based on the historical logistics order information, further comprising:
judging whether the cabinet outlet rate parameter of the self-lifting cabinet characteristic is smaller than a set threshold value;
if yes, generating alarm information.
8. The method of selecting self-extracting features of any one of claims 1, 6 and 7, wherein the step of calculating an out-rate parameter for the self-extracting features of at least one dimension based on historical logistics order information is performed periodically.
9. An apparatus for selecting self-contained features, comprising:
A calculation module configured to calculate, from historical logistics order information, a cabinet-out rate parameter of a self-cabinet feature of at least one dimension after the logistics order system receives the logistics order generation request, comprising: acquiring the in-and-out state of the logistics package according to the logistics track information of the historical logistics order information, acquiring the self-cabinet-lifting characteristics of at least one dimension according to the historical logistics order information, and calculating a cabinet rate parameter according to the self-cabinet-lifting characteristics of at least one dimension and the in-and-out state of the logistics package based on the historical logistics order information; the out-of-cabinet state of the logistics package is taken out by a user;
Wherein the self-extracting cabinet feature comprises one or more of the following dimensions: the method comprises the steps of providing a self-picking cabinet provider, information of a city area where the self-picking cabinet is located, informing a user of a goods taking mode, whether the self-picking cabinet is charged, the size of the self-picking cabinet, the number of the self-picking cabinets and corresponding crowds of the self-picking cabinets, wherein the cabinet outlet rate parameter represents the ratio of the number of the packages which are taken out of the cabinet to the number of the packages which are taken into the cabinet in a set cabinet outlet time difference under the self-picking cabinet characteristics of each dimension;
And the selection module is configured to select the self-cabinet feature according to the cabinet outlet rate parameter of the self-cabinet feature and send the selected self-cabinet feature to the logistics order system so as to generate a logistics order according to the selected self-cabinet feature.
10. An electronic device, the electronic device comprising:
A processor;
A memory having stored thereon a computer program which, when executed by the processor, performs:
A method of selecting self-extracting features as claimed in any one of claims 1 to 8.
11. A storage medium having a computer program stored thereon, the computer program when executed by a processor performing:
A method of selecting self-extracting features as claimed in any one of claims 1 to 8.
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